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Int. J. Internet Marketing and Advertising, Vol. 7, No. 4, 2012

Exploring social media marketing strategies in SMEs Iryna Pentina* and Anthony C. Koh Department of Marketing and International Business, University of Toledo, 2801 W. Bancroft St. Toledo, OH 43606-3390, USA Fax: 419-530-4610 E-mail: [email protected] E-mail: [email protected] *Corresponding author Abstract: This paper explores the emerging consistencies in the implementation of social media marketing by SMEs and classifies these recurring patterns into a taxonomy of managerially relevant strategic types. The empirical method of cluster analysis is applied to self-reported data by marketing executives to derive a typology of three dominant social media marketing strategic patterns. Calculative pragmatists, cautious watchers, and proactive strategists exhibit significant differences in the implementation of social media venues, perceived benefits of social media, utilised tactics, and performance. Cluster membership is also associated with industry type and firm size, as well as companies’ goals and reasons for adopting SMM. Keywords: social media marketing; SMM; small and medium-size enterprises; SMEs; strategy. Reference to this paper should be made as follows: Pentina, I. and Koh, A.C. (2012) ‘Exploring social media marketing strategies in SMEs’, Int. J. Internet Marketing and Advertising, Vol. 7, No. 4, pp.292–310. Biographical notes: Iryna Pentina is an Assistant Professor at the University of Toledo. Her research interests include social and interactive marketing, applicability of marketing theory to online sales situations, internet retailing, and virtual communities. She has published in the European Journal of Marketing, Journal of Retailing, Journal of Electronic Commerce Research, European Journal of Innovation Management, Journal of Consumer Behaviour, Journal of Customer Behaviour and others. Anthony C. Koh is Chair and Professor in the Department of Marketing and International Business, University of Toledo. His major research works have appeared in several publications, including International Marketing Review, Journal of Business Research, Journal of Global Marketing, Journal of the Academy of Marketing Science, Journal of Teaching in International Business, International Business Review, and the Journal of Electronic Commerce Research and others.

Copyright © 2012 Inderscience Enterprises Ltd.

Exploring social media marketing strategies in SMEs

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293

Introduction

According to BIA/Kelsey (2012), a consultancy, marketing expenditures on social media in the USA are expected to grow 21% annually and reach $9.8 billion in 2016, making it the fastest-growing marketing channel in the world. This trend reflects the paradigm shift within advertising and marketing communications industry: from one-way, ‘cluttered’ mass media to interactive, narrowly targeted approaches and towards synergistic integration of all company communications. Social media marketing (SMM) involves initiating viral consumer-to-consumer communications by creating company/brand customer communities and managing fan pages, promotions and public relations within popular social networks (Facebook, YouTube, and Twitter). This medium appears to be especially advantageous for small and medium-size enterprises (SMEs) due to their greater flexibility and higher need to contain marketing communications costs (Harris and Rae, 2009). Indeed, Media Life Magazine predicts small businesses spending on social media to reach $7.8 billion by 2016 (Vasquez, 2012). Additionally, IBMs recent CEO survey reports that 50% of small and mid-size businesses plan to use social media for marketing in the next three years (Casey, 2012), and 43% of the Inc., 500 companies believe that social media are very important to their marketing strategy (Sherman, 2012). While the advantages of SMM are strongly supported by experts, the decision to adopt this new marketing technology by SMEs is not automatic (Drossos et al., 2011): challenges include integrating social media into overall marketing mix, developing measurement metrics to estimate SMM effectiveness, and mitigating the risk of potential negative viral spread damaging a company’s reputation (eMarketer, 2011). To overcome these challenges, companies need to develop clearly identified SMM goals and strategies, determine systematic objectives for each social media venue, and define behaviours and tactics to address these objectives. Most of the existing theoretical and applied research on SMM in SMEs is case-based and anecdotal, describing best practices, innovations, and experiments with fan pages, Twitter parties, and designer contests (McCorvey, 2010). However, with increasing adoption of social media by businesses and their growing experiences with ‘muddling through’ various tactics and techniques, it appears possible to identify the emerging consistencies, and classify these recurring patterns into managerially relevant strategic types. Classification has long been considered an important building block of scientific inquiry (Carper and Snizek, 1980). In the strategy literature, classifications and taxonomies help organise complex phenomena and provide comprehensive representation of interrelated and recurring decision patterns (Hambrick, 1984). In marketing, classifications are widely used not only in theory development (e.g., types of advertising effects and categories of new product adopters), but also in practice (e.g., market segmentation). Therefore, arriving at an inductive classification of emerging social media strategies in SMEs can contribute to both important managerial implications and theory development in the areas of marketing strategy and marketing communications under the current conditions of technological turbulence and unprecedented growth of consumer power. This paper develops a taxonomy of social media strategies in SMEs based on cluster analysis of self-reported SMM usage data by marketing executives. It also explores the relationships between company characteristics and cluster membership, and assesses association of each inductively identified strategic approach with performance indicators. In the remainder of the paper, we provide an overview of the

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I. Pentina and A.C. Koh

relevant literature, describe data collection and testing methods, report and discuss the results, and provide conclusion, managerial recommendations, and suggestions for future research.

2

Social media and strategy

Ongoing developments in Web 2.0 and 3G/4G technologies have created a major paradigm shift in business-to-customer relationships: a shift in information control. Customers are no longer passive ‘receivers’ of company and brand-related marketing messages. Instead, they are engaged in initiating conversations with and providing feedback to businesses, as well as in creating and sharing content among themselves. Social media sites allow users to create and share personal profiles, establish and develop new connections, and provide and acquire information in an interactive manner (Boyd and Ellison, 2008). Open access to other members’ contacts provides consumers unprecedented opportunities to control the process of marketing communications by exponentially spreading viral messages about products, brands, and/or customer service that can be either detrimental or beneficial to any business. Given their remarkable size and growing marketing potential (e.g., Facebook with its 850 million members commands a 20% share of the US online advertising), social media are acquiring strategic significance for companies that appreciate their capacity for targeting, promotion, public relations, and market research (Drossos et al., 2011). While certain successes with using SMM are widely publicised, and the advantages of using these media by small and medium businesses are extensively discussed, the selection of social media venues, the extent of their adoption, and objectives for each selected venue, are not uniform. In fact, according to the joint study by MIT Sloan Management Review and Deloitte, only about 15% of companies with between 100 and 1,000 employees are actually present on social networks (Sherman, 2012). Other surveys find that some SMEs do not use social media at all because they considered this a waste of time (Economist, 2010). Given the broad variability of social media adoption behaviours, identifying emergent patterns in SMM implementation and associating them with company characteristics, objectives, and outcomes may provide important practical and theoretical contributions to SMM strategy development. Strategy is generally concerned with achieving a competitive advantage (Slater and Olson, 2001). The two most widely accepted classifications of strategic approaches are based on ways to enter a new market (adopt a new technology) (Miles and Snow, 1978) and to compete in an existing market (Porter, 1980). According to the Miles and Snow (1978) classification, Prospector firms continually seek, identify and embark on new opportunities, Defenders tend to protect their position in existing markets, Analysers adopt a gradual (follower/imitator) approach to adopting a market/technology, and Reactors adapt to change only under environmental pressure. Porter’s (1980) strategic types of Cost Leaders and Differentiators describe competition in existing markets, thus relating more to the Defender category of Miles and Snow (1978). While other strategic typologies have been proposed in the literature (Ansoff and Stewart, 1967; Freeman, 1974), the one by Miles and Snow has been most widely used in empirical research (Zahra and Pearce, 1990). This typology simultaneously considers the


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structure and the process necessary for the realisation of business strategy and reflects a complex view of both organisational and environmental characteristics (Smith et al., 1989). It has been validated in empirical studies in different industrial contexts (Hambrick, 1983), and has shown applicability for SMEs (Aragon-Sanchez and SanchezMartin, 2005). The development of information systems and technology strategy, as well as e-commerce strategy have traditionally followed the existing business strategy techniques and reflected the identified strategic typologies (Goldsmith, 1991). For example, the Miles and Snow typology was found useful in predicting the relationship between technological deployment (IS department’s impact, management style, technological architecture, learning processes, etc.) and organisational performance. The analysis of survey responses by top managers of 223 Canadian firms representing diverse industries showed that an inward focus of technological deployment positively affected Prospector firms’ performance, while an outward focus contributed directly to the Analysers’ performance (Croteau and Bergeron, 2001). In the domain of electronic commerce, higher profitability was recorded for companies that aligned their electronic commerce strategy with the overall business strategy type. For example, Defenders that used e-commerce to support successful existing product lines by maintaining quality and creating efficiencies, displayed comparable performance to Analysers that employed e-commerce to launch new products by leveraging the reputation of respected brands (Kearns, 2005). In the area of e-business strategy, Raymond and Bergeron (2008) found that different e-business strategies are appropriate for each type of a SMEs business strategy and, when such a strategic alignment exists, firms exhibit higher performance in terms of financial indicators, growth and productivity. In particular, it has been shown that Defender-type SMEs perform better when focusing on e-communication and transactional e-business capabilities, while Analysers should add e-intelligence, and Prospectors – e-collaboration to their e-business capabilities to achieve optimal performance (Raymond and Bergeron, 2008). The four strategic types have also been linked to distinctive marketing competencies, suggesting a ‘superiority’ pattern of decreasing numbers of marketing competencies in pair-wise comparison of Prospectors, Analysers, Defenders and Rectors (Woodside et al., 1999). These generic strategic types have been paralleled in the marketing strategy research, with Aggressive Marketers, Mass Marketers, Marketing Minimisers, and Value Marketers closely resembling the Miles and Snow (1978) categories (Slater and Olson, 2001). It is plausible that these generic categories may also apply to SMM strategic decisions concerned with selecting and integrating venues to reach customers more effectively and efficiently than competitors. Anecdotal evidence suggests that some firms (e.g., retailers) are more interested in setting up storefronts on social networks, while others (e.g., business-to-business marketers) prefer to use social networks to advance their brand reputation and customer loyalty (eMarketer, 2010a). Still others (e.g., large services corporations) utilise social media mainly for customer research and do not limit their use to social networks (eMarketer, 2010b). However, no strategic typologies have been proposed to explain emergent patterns in companies’ utilisation of SMM. The current study addresses this gap in social media strategy research by identifying consistent patterns in SMM implementation by SMEs and associating them with respective company characteristics and SMM performance.

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3


Description of the study

The goal of this study was to develop and validate a taxonomy of SMM strategies currently employed by SMEs, and to identify company characteristics and possible differences in SMM performance related to following a particular strategy. To achieve this goal, the authors followed a standard procedure of the cluster analytic method (Ketchen and Shook, 1996; Slater and Olson, 2001). The empirical method of cluster analysis, used in marketing for identifying discrete categories (taxonomies), makes no prior assumptions about important differences within a population (Punj and Stewart, 1983). It is sometimes criticised for the ad hoc nature of clustering solutions, but appears to be particularly relevant for the nascent research in SMM where no prior research is available for deducing implicit relationships and hypotheses. The procedures of the instrument development, data collection, and analysis are described below.

3.1 Instrument development Due to the lack of scientific theoretical research in the area, the clustering variable of social media utilisation pattern was selected inductively, based on the review of existing reports and articles in practitioner literature, and was measured by the number and combination of social media tools implemented by SMEs. Similarly, based on the review of business press reports describing SMM adoption and practices, we developed a set of measurement items reflecting dominant reasons for adopting SMM (7 items), widely used SMM tactics (9 items), and major benefits obtained as a result of utilising SMM (12 items). In addition to evaluating the SMM performance by the measure of benefits obtained, the survey asked about the percentage of company sales achieved from using SMM. Other measures included company-related characteristics, such as the type of business industry and annual sales, as well as questions about respondents’ functional area and position in the company. The length of experience with SMM and the degree of outsourcing vs. developing SMM in-house were also assessed (see Appendix). All items were pretested with two social media consultants working directly with small and medium businesses on SMM implementation. Consequently, the items were clarified and adapted to reflect the differences between SMM adopters and non-adopters.

3.2 Data collection and sample characteristics The data for the study were collected from business executives of small and medium size companies in the Midwest who participated in two consecutive annual internet Marketing conferences sponsored by a Midwestern university. An identical procedure for data collection was followed for the 2009 and 2010 conferences. The attendees were requested to fill out a paper-and-pencil survey containing demographic and psychographic questions about the company, respondent’s position and functional area, as well as questions about reasons for adopting, practices, tactics, and obtained benefits of SMM (Appendix). Two versions of the survey instrument (for those who have and those who have not yet adopted SMM) were distributed to the attendees. The response rates in both years were acceptable for this type of survey procedure (Slater and Olson, 2001). In 2009, out of 110 executives in attendance, 65 (59%) returned completed surveys. In 2010, out of 160 attendees, 59 (37%) usable surveys were returned. After excluding eight surveys (responses of four participants who attended the conference in both years), the


297

total sample contained 116 completed surveys. Due to the exploratory character of this pioneering study and given the representative nature of the sample, the sample size was deemed acceptable for the purpose of detecting the phenomena of interest (and not for predicting or generalising purposes). Table 1

Sample characteristics with 2009 and 2010 sub-sample comparison statistics 2009 %

2010 %

Primary business

χ2

p

27.67

0.274

Combined sample, %

B2B manufacturer

22.6

26

24

Consumer service provider

17.8

22

20

Business service provider

12.7

16

14

Distributor

11.3

8

10

Retailer

9.4

6

8

Consumer brand manufacturer

4.6

4

4.3

Other

21.6

18

19.7

Annual sales

1.88

0.598

Less than $1 million

22.8

30.2

26

$1.01 to $10 million

35.1

27.9

32

$10.01 to $25 million

19.3

25.6

22

More than $25 million

22.5

16.3

Position in company

20 21.87

0.328

Middle management

47.7

46

47

Upper management

38.6

28

36

Other

13.8

20

17

Marketing and sales

73.8

76

75

Operations

18.5

10

14

IT

3.1

8

6

Other

4.6

6

5

Yes

66.2

54

60.8

No

33.8

46

39.2

Facebook

71

80

1.28

0.258

75

Twitter

57

48

0.903

0.342

53

Functional area

39.24

Social media marketing use

2.76

0.205

0.501

SMM implementation

You Tube

32

48

2.922

0.087

39

LinkedIn

57

68

1.468

0.226

62

Brand community on own site

26

18

1.074

0.3

23

Other

34

43

1.9

0.189

38

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Table 2

Descriptive statistics for SMM implementation-related items: comparison of adopters and non-adopters [mean (SD) and ANOVA tests]

Item*

ANOVA

SMM adopters

SMM nonadopters

F

p

Combined sample

3.96 (1.07) 4.09 (0.8)

3.37 (1.26) 3.47 (1.31)

2.7 3.5

0.108 0.078

3.69 (1.18) 3.81 (1.09)

3.61 (1.16)

2.89 (1.47)

3.1

0.086

3.29 (1.35)

3.96 (1.07) 4.09 (0.9) 4.09 (1.04)

3.37 (1.26) 3.56 (1.29) 3.9 (1.21)

2.7 2.4 0.3

0.108 0.129 0.589

3.69 (1.18) 3.85 (1.11) 4.0 (1.11)

4.6 (0.6)

4 (0.97)

0.61

0.432

4.3 (0.85)

3.17 (1.47)

3.55 (1.1)

0.88

0.353

3.35 (1.31)

3.61 (1.08)

3.37 (1.12)

0.5

0.483

3.5 (1.09)

3.23 (1.31)

3.16 (1.3)

0.03

0.866

3.2 (1.29)

3.2 (1.41) 3.4 (1.35)

3.1 (1.48) 3.21 (1.24)

0.02 0.23

0.820 0.560

3.15 (1.3) 3.31 (1.27)

3.5 (1.1)

3.17 (1.43)

0.79

0.380

3.3 (1.09)

4.7 (0.47)

4.76 (0.54)

0.19

0.670

4.73 (0.5)

4.35 (0.78) 3.48 (1.24)

4.19 (0.81) 3.35 (1.35)

0.43 0.11

0.520 0.750

4.27 (0.79) 3.42 (1.28)

3.77 (1.19) 3.91 (1.08) 3.87 (1.18)

3.86 (1.28) 3.81 (0.87) 3.5 (1.05)

0.05 0.12 1.16

0.820 0.730 0.290

3.81 (1.22) 3.86 (0.98) 3.7 (1.12)

Reasons for implementing SMM To reduce advertising expenses To be an early player in social media More competitors and consumers are using it To break through advertising To better reach target market To try a new approach SMM tactics Creating and maintaining account on SM site Brand community/forum on your own site Customer reviews/rating on your own site Advertising on social networks sites Increasing traffic to your website Increasing traffic to your physical location Monitoring chatter on social networks SMM benefits Increased brand awareness of your products Spread marketing message Enabled customer participation in product development Obtained customer feedback Enabled better marketing Improved customer support

Note: *All items measured on a scale from 1(strongly disagree) to 5 (strongly agree).

The combined sample represented a wide variety of industries (Table 1), including consumer and business services, business-to-business manufacturing, distribution, and retailing, with 80% reporting annual revenues of less than $25 million [qualifying for the revenue-based SME definition, Altman and Sabato (2005)]. A great majority (83%) of the respondents held decision-making positions of owner, upper- or middle-manager in their companies, which made them appropriate subjects for assessing strategic decision-making practices. Over 81% represented functional areas of marketing and information technology that are mainly related to the adoption and use of SMM. About two-thirds (60.8%) of the sample were using SMM at the time of the conference, with the


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remaining 39.2% admitting they had never used social networks for marketing before. No significant differences between the 2009 and 2010 respondents in terms of company size, characteristics, and social media adoption were found (Table 1). The comparison of SMM adopter and non-adopter groups (Table 2) showed no significant differences among them in terms of reasons to implement SMM, dominant tactics to employ when using SMM, and benefits obtained (or expected) from the SMM utilisation. Additionally, the two groups did not differ in terms of primary business (χ2 = 24.97, p = 0.41) and company size (χ2 = 3.18, p = 0.37), which allowed us to combine the sample for the analysis of emerging strategic patterns in SMM practices by SMEs.

3.3 Data analysis and results We used SPSS 17.0 software to perform a hierarchical cluster analysis employing the between-groups linkage method with the squared Euclidian distance measure. This method is appropriate for exploratory research with no prior specification of the desired number of clusters (Punj and Stewart, 1983). Since our goal was to arrive at categories of SMEs with discrete SMM strategies, the combination of implemented (intended for implementation) SMM tools (item 6 in the questionnaire) was set as the clustering criterion. Five binary variables representing use (value = 1) or non-use (value = 0) of Facebook, Twitter, You Tube, LinkedIn, and own community were entered as clustering variables. We conducted separate cluster analyses for the 2009 and 2010 sub-samples in order to assess the stability of the identified cluster solutions (Slater and Olson, 2001). Based on the dendrograms and the agglomeration schedules, the cluster analyses of both 2009 and 2010 data optimised at three clusters. Cross-tabulations comparing cluster membership to the SMM implementation patterns (clustering variable) supported the similarity of cluster solutions for both sub-samples (Table 3), demonstrating the reliability of the clustering variable. This finding, along with the absence of significant differences between the samples in other measured aspects (Table 1), allowed us to combine the two sub-samples for further analyses. Table 3

Cluster membership and social media combinations: cross-tabulation results Facebook

2009

2010

Combined sample

χ2 Cluster 1 Cluster 2 Cluster 3 χ2 Cluster 1 Cluster 2 Cluster 3 χ2 Cluster 1 Cluster 2 Cluster 3

20.7** 67% 13% 96% 9.41** 70% 33% 96% 31.39** 68% 18% 96%

Twitter 28.2** 42% 0% 96% 7.73* 35% 0% 67% 32.01** 40% 0% 81%

You Tube 52.99** 0% 0% 88% 50.0** 0% 0% 100% 103.19** 0% 0% 94%

Notes: *differences among clusters are significant at p < .05 **differences among clusters are significant at p < .01.

LinkedIn 1.54 58% 38% 63% 0.48 70% 68% 68% 1.41 63% 46% 65%

Own brand community 35.88** 0% 100% 38% 19.51** 0% 100% 25% 56.06** 0% 100% 31%

300 Table 4

I. Pentina and A.C. Koh Cluster membership and SMM implementation: means, SDs and ANOVAs

A. Reasons to adopt SMM To reduce advertising spending

To be an early player in social media marketing More competitors and consumers are using it To break through advertising clutter

To better reach our target market

To try a new approach

Cluster 1 Cluster 2 Cluster 3 Cluster 1 Cluster 2 Cluster 3 Cluster 1 Cluster 2 Cluster 3 Cluster 1 Cluster 2 Cluster 3 Cluster 1 Cluster 2 Cluster 3 Cluster 1 Cluster 2 Cluster 3

B. Tactics used with SMM Creating and maintaining a social networks account Increasing traffic to your website

Increasing traffic to your physical location Creating a brand community/customer forum on your website Providing customer reviews and ratings on your site Monitoring chatter about your company on social networks Placing advertising on social network sites

Cluster 1 Cluster 2 Cluster 3 Cluster 1 Cluster 2 Cluster 3 Cluster 1 Cluster 2 Cluster 3 Cluster 1 Cluster 2 Cluster 3 Cluster 1 Cluster 2 Cluster 3 Cluster 1 Cluster 2 Cluster 3 Cluster 1 Cluster 2 Cluster 3

Mean

SD

F

Sig.

4.23* 2.73 3.21 2.75 3.09 4.06* 2.79 4.09* 3.04 3.86* 2.82 3.40 3.91* 2.91 3.08 3.29* 4.18 4.08

0.63 0.90 0.90 0.99 1.30 1.02 1.11 1.22 1.05 0.88 0.98 0.98 1.00 0.83 1.03 1.14 0.98 0.94

31.005

.000

21.065

.000

6.553

.002

7.024

.001

10.841

.000

8.768

.000

Mean

SD

F

Sig.

4.00 3.82 4.40 3.55 3.14 3.07 3.67 3.03 3.23 2.89* 4.09 3.78 3.57 3.27 3.13 3.06 3.55 3.14 3.09 2.55 3.64*

0.97 0.75 0.82 1.41 1.19 1.21 1.278 1.204 1.09 1.00 0.83 1.24 1.04 1.01 1.25 1.27 1.40 0.99 1.26 0.82 1.28

3.375

.038

2.780

.075

5.013

.033

10.874

.000

1.918

.152

4.167

.018

4.688

.011

Note: *Differences among clusters are significant at p < .05.

Exploring social media marketing strategies in SMEs Table 4

301

Cluster membership and SMM implementation: means, SDs and ANOVAs (continued)

C. Benefits attributed to SMM implementations Increasing brand awareness of your products/services Spread marketing message

Enabled customer participation in product development Obtained customer feedback

Enabled better marketing research

Improved customer support

Mean

SD

F

Sig.

9.509

.000

0.329

.720

5.025

.008

13.786

.000

3.483

.034

1.899

.155

Cluster 1

4.77

0.572

Cluster 2

3.82*

1.079

Cluster 3

4.73

0.676

Cluster 1

4.30

0.933

Cluster 2

4.18

1.168

Cluster 3

4.15

1.052

Cluster 1

3.27

1.070

Cluster 2

2.82

0.982

Cluster 3

3.81*

1.197

Cluster 1

3.27*

1.183

Cluster 2

4.27

0.786

Cluster 3

4.33

0.996

Cluster 1

3.62

1.240

Cluster 2

4.55*

0.688

Cluster 3

3.52

1.185

Cluster 1

3.89

1.056

Cluster 2

3.27

1.348

Cluster 3

3.56

1.201

Note: *Differences among clusters are significant at p < .05. Table 5(a) Cluster membership and SMM percentage of sales: cross-tabulation results What percent of sales comes from SMM?

1%–5 %

5.1%–10%

10.1%–25%

> 25%

Cluster 1

69%

35%

0%

0%

Cluster 2

100%

0%

0%

0%

Cluster 3

66.7%

23.8%

7.1%

2.4%

Table 5(b) Cluster membership and SMM outsourcing: cross-tabulation results Do (would) you develop SMM in-house or outsource?

In-house

Outsource

Both

Cluster 1

18.2%

27.3%

54.5%

Cluster 2

27.3%

45.5%

27.3%

Cluster 3

58.8%

16.7%

24.6%

As expected, cluster analysis of the combined sample optimised at three clusters (similar to the two sub-sample solutions) that significantly differed in SMM implementation patterns. Cluster 1 members preferred Facebook as SMM of choice and employed LinkedIn and Twitter to a certain extent. Cluster 2 members were more likely to create a brand community on their own website, and used LinkedIn and Facebook to a lesser extent. Finally, cluster 3 representatives reported using all the listed SMM tools to a high extent (Table 3).

302


Cross-tabulations with chi-square statistics revealed significant differences in the primary business characteristic (χ2 = 16.93, p = 0.01), and company size measured by annual sales (χ2 = 15.71, p = 0.015) among the three clusters. Cluster 1 was dominated by smaller retailers; cluster 2 consisted mainly of large business-to-business companies, and cluster 3 combined various businesses of diverse company sizes, with consumer services and consumer manufacturing represented to a slightly greater extent. We utilised ANOVA and post-hoc multiple comparison tests to compare cluster membership with the reported reasons for adopting SMM, dominant SMM tactics employed by the businesses, as well as the perceived benefits of SMM utilisation (Table 4). We also compared cluster membership with the reported percentage of overall sales resulting from SMM use [Table 5(a)], and SMM outsourcing vs. in-house development by conducting crosstabulation procedures [Table 5(b)]. As a result, we were able to arrive at the following unique cluster solutions. Cluster 1: calculative pragmatists (56 companies). Representatives of this cluster are mainly involved in retail business, with the majority reporting annual sales from below $1 million to $10 million. They adopt SMM to both better reach their target market by breaking through advertising clutter, and to cut advertising expenses. These companies were early players in SMM, and have used them selectively, with major emphasis on Facebook, followed by LinkedIn and Twitter. They utilise these sites mainly to increase traffic to their physical locations and to reinforce customer engagement by encouraging product reviews and discussions. They employ both in-house capabilities and outside vendors to maintain their social media presence, and consider major benefits of SMM to be creating brand awareness and spreading marketing message. They assess the impact of SMM to range from 1% to 10% of overall sales. Cluster 2: cautious watchers (11 companies). These businesses are mostly business-to-business service providers and manufacturers, with annual sales from $10 million to over $25 million. They utilise SMM mainly to try a new approach, as well as due to pressure from their customers and not to lag behind their competitors. They were the earliest adopters of social media, but use them sparingly, emphasising brand communities on their own sites, and using LinkedIn and Facebook sites to a lesser extent. Their dominant tactics include maintaining customer forums and brand communities, and monitoring chatter on social networks. They tend to outsource their SMM, and consider major SMM benefits to be obtaining customer feedback, conducting marketing research, and spreading marketing message. They appraise the impact of SMM on total sales to range between 1% and 5%. Cluster 3: proactive strategists (48 companies). This cluster is mainly represented by consumer service providers and consumer goods manufacturers, with a wide range of annual income from $1 million to more than $25 million. Their reasons for employing SMM include being an early player and trying a new approach to marketing. They were relatively late entrants to the SMM space, but appear to be the most enthusiastic by using all existing social media sites and tools. Their dominant tactics include creating social networks accounts for their brands, placing ads on social networks sites, and creating brand communities on their own websites. They mainly employ in-house capabilities for SMM and perceive the most important benefits from SMM to be obtaining customer feedback, enabling customer participation in product and service development, as well as creating brand awareness and spreading marketing message. Their estimate of SMM impact on sales is very broad and ranges from 1% to 25%.


4

303

Discussion and implications

This study has contributed to the theory and practice of social media strategy development in SMEs by performing an exploratory cluster analysis based on the implementation patterns of SMM tools (clustering variable). The hierarchical cluster analysis optimised at a three-cluster solution for both the 2009 and 2010 sub-samples, confirming the stability and reliability of the selected clustering variable for arriving at unique clusters. Consequent hierarchical cluster analysis of the combined sample confirmed the usefulness of the selected clustering variable in arriving at similar clusters of companies based on their SMM tools implementation patterns. ANOVA and crosstabulation tests demonstrated the usefulness and validity of the three clusters by showing significant differences in company characteristics and SMM tactics, and performance among the three identified strategy clusters. In particular, companies representing different industries have been shown to engage in dissimilar SMM practices, pursue diverse goals, and obtain different benefits. Calculative pragmatists (mainly represented by mid-size retailers) pursue the SMM strategy very similar to Miles and Snow’s (1978) Analysers: they exhibit a results-based analytical approach to engaging in social media and are closely monitoring their bottom-line. One of the main reasons for implementing SMM for these firms is cutting advertising expenses, and one of the major tactics they use is driving traffic to their physical locations, in an attempt to reduce ‘channel shift’ and attain maximum synergy among their distribution channels. Although the major benefits they claim from utilising social media are at the top of the ‘promotion funnel’ (developing brand awareness and spreading marketing message), their efforts at customer engagement (through social networks) may help account for the up to 10% of SMM-driven sales. Like Miles and Snow’s (1978) Analysers, calculative pragmatists adopt a follower approach to SMM, waiting and selecting the tools that have been shown to deliver the needed performance. Cautious watchers in this study (comprising larger business-to-business firms) do not appear to have a direct counterpart in the Miles and Snow (1978) typology, and can be placed between Defenders and Reactors based on their SMM practices and adoption pattern. Similarly to Reactors, they implement social media mainly on a trial basis, sometimes under pressure from their customers and competitors. Like Defenders, they prefer more conservative, tried and true tools, such as customer forums and communities on their own websites. These companies do not appear to consider SMM a competitive strategic choice: rather it is utilised for protecting their current position through market research, reputation monitoring, and customer feedback. Consequently, the bottom-line impact of SMM is neither expected, nor highly evaluated (1% to 5% of sales). This SMM approach is similar to the process of ‘isomorphism’, when organisations develop certain non-strategic capabilities to resemble other organisations facing similar environmental conditions (Pan et al., 2007). Adopting SMM may be considered necessary for avoiding a competitive disadvantage, and thus represent not an investment, but an unavoidable cost for these firms. Proactive strategists (comprising a wide range of industries, with slightly higher number of consumer-services firms) closely resemble the Miles and Snow’s (1978) category of Prospectors: they enthusiastically embrace and experiment with all available social media tools in search for new opportunities. Apparently, these companies consider SMM a dynamic strategic capability that may confer a competitive advantage, and therefore prefer to invest in developing it in-house. Proactive strategists are the closest to

304


achieving customer engagement with their brands through utilising both the less typical You Tube channel and the more conservative customer forums on their own websites. Through experimentation and innovation, this strategic group is more likely to pursue Porter’s (1980) differentiation strategy as the SMM matures and its dynamics become predictable for developing a more stable strategic fit. The findings of this study show that social media adoption for marketing purposes by SMEs follows identifiable patterns, potentially determined by each company’s characteristics and objectives. These strategic patterns are somewhat similar to the generic strategy types recognised in business and marketing. Understanding which strategic path to pursue, what tactics to employ, and what benefits to expect based on individual company’s situation and aspirations will greatly assist managers in allocating resources and setting objectives with respect to SMM. This means that although SMEs are believed to rely predominantly on less formalised, ‘emergent’ strategy implementation (Sainidis et al., 2001), certain amount of planning and analysis is in order. For example, depending on the type of industry, companies may pursue different paths in generating value from SMM. While retailers may strive for short-term sales results, consumer goods manufacturers may attain savings from providing customers an opportunity to help each other on customer forums. Moreover, while almost all companies benefit financially by delegating crisis management and customer service to Twitter, only consumer goods and services companies may gain higher brand awareness through setting up fan pages and improved search engine accessibility by using videos and blogs. In the same vein, companies should be selective in terms of key performance indicators they use to assess SMM results. Metrics such as the number of viewers, visitors, friends, or followers do not automatically translate to higher conversions, order value, or sales, but may be useful for gauging increases in brand awareness and attitude. Thus, understanding which metrics are most indicative of goal achievement is an important priority. Another important strategic challenge that appears to be addressed only by multi-channel retailers, is ascertaining SMMs contribution to the whole marketing communications mix. Other SMEs should dedicate more attention to strategic balancing of SMM with other marketing communications. Our findings provide value to social media vendors and service providers by outlining potential target market segments, and profiling SMEs that may be interested in outsourcing various SMM functions. In particular, Cautious Watchers, although less enthusiastic about SMM, may be a good target market for outsources solutions, since they do not perceive competence in social media as part of their strategic capabilities. These may be the best candidates for on-demand ‘in the cloud’ offerings that do not require long-term commitments and can be modified at short notice. Calculative pragmatists may be approached with cost-efficient solutions that allow them some control over proprietary customer relationship management data, while proactive strategists may be more interested in cutting-edge offerings that would allow them a head start without overbearing capital-intensive investments.

5

Conclusions, limitations and future research

In spite of the existing scepticism regarding SMM effectiveness and measurability, ever increasing number of companies worldwide plan to incorporate it into their marketing programs and to shift resources away from traditional to SMM. The 2012 Internet


305

Advertising Statistics Report by eConsultancy shows that 61% of more than 1,000 surveyed marketers worldwide plan to increase investment in social media in 2012 (Econsultancy, 2012). Forrester (2011) research also predicts that social media will see the steepest growth of any channel, exceeding $3 billion by 2014. In light of rapidly growing adoption of SMM by SMEs, it is important to uncover trends and patterns in SMM strategic decisions, and provide guidance to marketing managers regarding their effectiveness. This paper represents one of the first studies of strategy in the SMM area. It contributes to the existing literature by empirically deriving a typology of strategic patterns and illustrating their reliability and validity in terms of differential effects of SMM strategic choices on perceived benefits, utilised tactics, and differential performance. It also suggests that cluster membership may be associated with such company characteristics as industry type and size, as well as companies’ goals and reasons for adopting SMM. These findings are useful in terms of providing guidance to SME marketing managers and laying initial theoretical grounding for future research. The findings of our study should be generalised with caution due to the limited sample size and geographic concentration. Although representative of SMEs in terms of the industry and size variety, this sample was sufficient for exploratory, but not predictive purposes. Scarcity of existing research in the area determined the inductive approach of this study, and resulted in arrival at clusters exhibiting distinct strategic patterns. These initial cluster solutions can serve as a starting point for more causal and predictive research in the area. Future research can test the generalisability of the proposed typology on a broader sample of SMEs. The identified strategic patterns should be further validated by large-scale investigations that would test their relationships with antecedent company characteristics, and outcome variables other than percentage of sales and perceived benefits. Moderating effects of technological turbulence or overall industry membership could also be investigated. Another interesting research possibility is to determine the length of time required for each new SMM tactic to work and the resulting resolution of measurement timing challenges. Due to the cross-sectional research design and single-source self-report data, no causality can be attributed to our findings. It is possible that unintended spontaneous ‘muddling though’ social media experimentation was rationalised post factum in the executives’ responses, and the SMM implementation patterns were adopted incrementally, without prior intentions or objectives. In order to better understand the process of strategy-making, a longitudinal investigation is in order that would compare the ‘intended’ to the ‘realised’ and ‘emergent’ (Mintzberg and Waters, 1985) SMM strategies in SMEs. An interesting question in this area is the correspondence between strategic company types and strategy-development processes: are calculative pragmatists and cautious watchers more deliberate (planning their steps in detail) than proactive strategists who are more flexible and responsive to the rapidly evolving reality?

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Appendix Internet marketing conference participant survey 1

What is your primary business? a

2

Consumer brand manufacturer

b

B2B manufacturer

c

Consumer service provider

d

Business service provider

e

Distributor

f

Retailer

g

B2B manufacturer

h

Other __________________________________.

What is your position within the company? a

Upper management

b

Middle management

c

Other _____________________________________________.

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Internet marketing conference participant survey (continued) 3

What is your functional area? a

4

5

6

b

IT

c

Operations

d

Other _________________________________________________.

Does your company currently employ social media marketing (SMM)? a

Yes

b

No

Do you currently (or would you in the future) develop SMM in-house or outsource it to a third-party? a

Develop in-house

b

Outsource

c

Both

d

Other _________________________________________________.

What social networks do (would) you participate in? Please select all that apply. a

7

8

Face Book

b

Twitter

c

You Tube

d

LinkedIn

e

Community on your company’s website

f

Other ___________________________________.

What is the annual sales range of your business? a

Less than $1 million

b

$1 million to $10 million

c

$10.1 million to $25 million

d

More than $25 million

What percent of your sales comes (may come) from social media marketing? a

9

Marketing and sales

1% to 5%

b

5.1% to 10%

c

10.1% to 25%

d

More than 25%

When did you start using (learned about) social media marketing? a

Less than 1 year ago

b

Between 1 and 3 years ago

c

Between 3 and 5 years ago

d

More than 5 years ago


309

Please circle the number that most clearly reflects your opinion Rating code: 5 = Strongly agree (SA) 4 = Agree 3 = No opinion 2 = Disagree 1 = Strongly disagree (SD) 10

What are (would be) the major objectives for using social media by your company? To increase brand awareness of your products/services To develop higher awareness of your company within your target market To improve brand/company reputation To identify and attract new customers To stay engaged with current customers To develop strong relationships with current customers To enable better marketing research To spread marketing message To increase sales To enable customers to participate in product/service development To obtain customer feedback To improve customer support

11

4 4

3 3

2 2

1 1

5 5 5 5 5 5 5 5 5 5

4 4 4 4 4 4 4 4 4 4

3 3 3 3 3 3 3 3 3 3

2 2 2 2 2 2 2 2 2 2

1 1 1 1 1 1 1 1 1 1

SA

SD

5

4

3

2

1

5 5 5 5 5 5 5 5

4 4 4 4 4 4 4 4

3 3 3 3 3 3 3 3

2 2 2 2 2 2 2 2

1 1 1 1 1 1 1 1

What are the reasons your company uses (would use) social media marketing? To reduce advertising expenses To be an early player in social media Because competitors using it/not to appear a technology laggard Because more consumers are using it To break through advertising clutter To better reach our target market To try a new approach

SD

5 5

What social networks marketing tactics (would) work best for your business? Creating your own account on a social media site, maintaining it and posting status updates Increasing the number of your company’s fans/followers Increasing traffic to your website Increasing traffic to your physical location Creating a brand community/customer forum on your own site Providing customer reviews and ratings opportunity on your site Monitoring chatter about your company on social networks Placing advertising on social networks sites Increasing the number of your company’s fans/followers

12

SA

SA 5 5 5 5 5 5 5

4 4 4 4 4 4 4

SD 3 3 3 3 3 3 3

Notes: Two versions of the questionnaire were utilised. Version 1 for adopters of SMM contained active verbs, like ‘currently use’. Version 2 for non-adopter of SMM contained verbs reflecting future intention, like ‘would use’. For parsimony, the survey instrument in this Appendix integrates both versions, in which the version for non-adopters of SMM is reflected in the use of verbs within parentheses.

2 2 2 2 2 2 2

1 1 1 1 1 1 1

310


Please circle the number that most clearly reflects your opinion (continued) Rating code: 5 = Strongly agree (SA) 4 = Agree 3 = No opinion 2 = Disagree 1 = Strongly disagree (SD) 13

A major problem with SM marketing for our company is (would be) It takes up more time than we expected It takes up more resources than we expected It creates higher possibility for negative publicity It may hurt our image It is not achieving its goals

14

SA 5 5 5 5 5

4 4 4 4 4

The key SM performance indicators for your company are (would be) # of new visitors to our social media site # of repeat visitors to our social media site # of new visitors to our company website # of repeat visitors to our company website Quality of new sales leads Quality of consumer insights Quantity of sales increases

SD 3 3 3 3 3

2 2 2 2 2

SA 5 5 5 5 5 5

4 4 4 4 4 4

1 1 1 1 1 SD

3 3 3 3 3 3

Notes: Two versions of the questionnaire were utilised. Version 1 for adopters of SMM contained active verbs, like ‘currently use’. Version 2 for non-adopter of SMM contained verbs reflecting future intention, like ‘would use’. For parsimony, the survey instrument in this Appendix integrates both versions, in which the version for non-adopters of SMM is reflected in the use of verbs within parentheses.

2 2 2 2 2 2

1 1 1 1 1 1